What is going on here?

 Radical Uncertainty
Decision-Making Beyond the Numbers

The question ‘What is going on here?’ sounds banal, but it is not. In our careers we have seen repeatedly how people immersed in technicalities, engaged in day-to-day preoccupations, have failed to stand back and ask, ‘What is going on here?’ We have often made that mistake ourselves.

This is precisely the question that Mervyn King and John Kay pose in their new book Radical Uncertainty. Terrific reading for lockdown days. Below, I've selected some statements:

 The difference between risk and uncertainty was the subject of lively debate in the inter-war period. Two great economists – Frank Knight in Chicago and John Maynard Keynes in Cambridge, England – argued forcefully for the continued importance of the distinction. Knight observed that ‘a measurable uncertainty, or “risk” proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all’

The title of this book, and its central concept, is radical uncertainty . Uncertainty is the result of our incomplete knowledge of the world, or about the connection between our present actions and their future outcomes. Depending on the nature of the uncertainty, such incomplete knowledge may be distressing or pleasurable. I am fearful of the sentence the judge will impose, but look forward to new experiences on my forthcoming holiday. We might sometimes wish we had perfect foresight, so that nothing the future might hold could surprise us, but a little reflection will tell us that such a world would be a dull place.
We have chosen to replace the distinction between risk and uncertainty deployed by Knight and Keynes with a distinction between resolvable and radical uncertainty. Resolvable uncertainty is uncertainty which can be removed by looking something up (I am uncertain which city is the capital of Pennsylvania) or which can be represented by a known probability distribution of outcomes (the spin of a roulette wheel). With radical uncertainty, however, there is no similar means of resolving the uncertainty – we simply do not know. Radical uncertainty has many dimensions: obscurity; ignorance; vagueness; ambiguity; ill-defined problems; and a lack of information that in some cases but not all we might hope to rectify at a future date. These aspects of uncertainty are the stuff of everyday experience.
Radical uncertainty cannot be described in the probabilistic terms applicable to a game of chance. It is not just that we do not know what will happen. We often do not even know the kinds of things that might happen.

Our ability as humans to deal with radical uncertainty is the product of our much greater capacity for social learning and greater ability to communicate relative to other species. We are social animals; we manage radical uncertainty in a context determined by the knowledge we have acquired through education and experience, and we make important decisions in conjunction with others – friends, family, colleagues and advisers.
Reference to the ‘wisdom of crowds’ makes an important point while missing another. The crowd always knows more than any individual, but what is valuable is the aggregate of its knowledge, not the average of its knowledge.

A known unknown

Coronavirus and the Limits of Economics
Why standard economic theories have no answers for this kind of crisis

You'll find an interesting article in FP

Economists have long made the distinction between uncertainty and risk. Uncertainty is typically understood as involving outcomes that cannot straightforwardly be assigned a probability, unlike risk. Economics offers limited resources to understand how to make decisions in the presence of fundamental uncertainty. But a still deeper form of uncertainty is one in which the possible outcomes cannot easily be anticipated at all. Such a wildly unpredictable outcome has come to be popularly known in recent years as a black swan event.

 The coronavirus pandemic might at first appear to have been such a black swan event, but that claim does not withstand scrutiny: The possibility of such a threat was long recognized by experts. This recognition led to scenarios being discussed at the highest levels of governments. The possibility of a pandemic was therefore a “known unknown” rather than an “unknown unknown.”

Consider that an economy cannot be separated from society: It is socially embedded. The notion that the economy can be analyzed independently of the public health, political, or social processes—often promoted by the dominant tradition in economics and reflected in general equilibrium theory—is shown by the pandemic to be not merely fragile but false.

PS D Rumsfeld stated:

Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don't know we don't know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.

Galeria Marlborough

Ara toca (prioritzar) (2)

La decisió d'ahir del NICE suposa tot un repte per a d'altres governs europeus. Va considerar que el fingolimod per a esclerosi múltiple no havia de ser finançat pel NHS. Destaco dos paràgrafs clau de la resolució:

In summary, the Committee believed that the manufacturer’s base case ICER for fingolimod of £55,600 per QALY gained compared with Avonex for population 1b was subject to considerable uncertainty and an underestimation of the most plausible ICER for the following reasons:

• Avonex is not an appropriate comparator for population 1b. Using more appropriate comparators such as best supportive care or Rebif-44 for population 1b increased the ICERs substantially. To establish the most plausible ICERs for population 2, a comparison with natalizumab would need to be considered.
• More plausible assumptions regarding the long term treatment effectiveness increased the ICERs.
• Inaccuracies in the administration costs employed in the model are likely to have led to an underestimation of the ICERs.
• Data chosen to model the natural history of disease progression were derived from a population that was unrepresentative of the current UK population with multiple sclerosis. This led to uncertainty in the model results.
• Utility data from the clinical trials should have been used in the model and supplemented by published sources only for estimates for higher EDSS scores not represented by the populations in the trials. This led to uncertainty in the model results.

The Committee concluded that an analysis that relied on a combined set of plausible assumptions (see section 4.17) would be certain to produce ICERs that substantially exceed the range it could consider to represent a cost-effective use of NHS resources. The most plausible ICERs for fingolimod for the treatment of relapsing–remitting multiple sclerosis in the base case population (population 1b) is likely to be above £94,000 per QALY gained compared with best supportive care and above £79,000 per QALY gained in the subgroup of population 1b in which people with rapidly evolving severe disease were excluded. Therefore fingolimod cannot be recommended as a cost-effective use of NHS resources.

Cal llegir el document sencer perquè esdevé més interessant comprendre l'avaluació de l'efectivitat abans que el cost-efectivitat. Les notícies que en sorgiran poden contenir biaixos interessats. Observo una preocupació per l'efectivitat que aporta i en canvi les notícies se centraran en el cost-efectivitat. Ara hi ha unes setmanes per avaluar aquesta decisió i després hi haurà la resolució definitiva.
El medicament ja està aprovat al mercat tant a UK com aquí i podria suposar un nou serial com va succeir amb Tysabri, si bé en aquell cas centrat en qüestions de seguretat.
L'esclerosi múltiple és una malaltia que demana noves teràpies però que hi ha dificultats fonamentals per l'abordatge. El NICE va mantenir un conflicte important amb els interferons ja fa uns anys. Ara amb aquesta decisió pot ser un pròleg de nova controvèrsia. Aquest conflicte es podria resoldre en primer lloc aportant dades sobre efectivitat o també canviant el preu, de fet el preu britànic és un terç inferior al dels USA, però no n'hi hauria prou. Podria ser que aquí la propera reunió de la comissió interministerial de preus ho aprovés sense cap anàlisi similar (preu aprox. tractament anual 22.000 euros). En definitiva, ara tocaria prioritzar sobre bases fonamentades i tinc la impressió que ho deixarem per un altre moment. Crec que per al regulador d'aquí tant li fa la decisió del NICE. Ara bé, i als ciutadans?.

Risk-sharing agreements for drugs (3)

 Characterization of the Pharmaceutical Risk‑Sharing Arrangement Process in Catalonia

Table 1

Uncertainty type, scope, and considered variables for drug assessment

Uncertainty type	Uncertainty scope	Considered variables
Clinical	Efficacy, effectiveness, and safety	Time frame
		Clinical trial phase
		Patient characteristics
		Primary endpoint
		Surrogate endpoints
		Active comparator
		Sensitivity analysis
		Statistical analysis
		Patient subgroup analyses
		Time frames for treatment follow-up
Financial	BI and CE	Indication extension and concretion
		Treatment regimen
		Potentially replaceable treatments
		Net financial impact of treatment inclusion/replacement
		Potential use extensions
		Other modifications in use of resources linked to new treatment
		Availability of CE or CU studies

Adapted from [14]

Vestits a mida (3)

The Combined Analysis of Uncertainty and Patient Heterogeneity in Medical Decision Models

Fa dues dècades es parlava de com la intel.ligència artificial s'aplicaria a la medicina. El cert és que aquella febre va passar i es van obrir noves escletxes en aquell edifici en construcció. Ara, que es porten els vestits a mida novament, acaba de publicar-se a Medical Decision Making un article que ofereix una nova aproximació a la presa de decisions amb incertesa. El text presenta complexitat, i l'exemple del final ho aclareix prou bé. Ens mostra com individualitzar les taules de risc cardiovascular, en definitiva com tractar l'heterogeneitat dels pacients i la incertesa dels paràmetres que estem analitzant. Destaco:

We explained how the analysis of patient heterogeneity and parameter uncertainty can inform medical decisions. Modeling patient heterogeneity is required to determine the optimal intervention for each patient. Modeling parameter uncertainty allows for value of information analyses to determine whether additional
research regarding a decision is justified.

En Weinstein et al. també es preocupen del mateix a Plos One, definitivament tornen els sastres i modistes.

PS. En Quim Monzó s'ha quedat de pedra quan el màgic Cambras ha fet un truc espectacular. Ha demanat que pensés un número d'una carta i a en Basté un pal, i l'ha endevinat, el 8 de cors. En Quim Monzó ha exclamat: "Tu ets molt bo". I ja no ha tingut més paraules. Comparteixo la sorpresa, puc confirmar-ho perquè l'any passat va fer el truc davant meu i encara estic perplex.

PS. Sentiset. Així és com anomenaven a Carles Sentís a La Publicitat. Ell mateix ho explicava a l'entrevista a Catalunya Radio que van emetre novament ahir. Persona i periodista únic, testimoni d'excepció del segle XX ens ha deixat. La forma com ell entenia el periodisme, també es va acabar fa dies. Quin abisme separa l'imperi Murdoch de la contribució de Sentís al periodisme!.Llegiu "Vint-i-vuit hores e Transmiserià" escrit l'any 32.

PS. El decàleg de Metges de Catalunya no passaria pel sedàs d'un codi d'ètica com el de l'American Medical Association. Al primer punt del decàleg s'aturaria. Diu:

Anteposa el teu criteri clínic i fes prevaler la qualitat assistencial. No diagnostiquis influenciat per criteris d’estalvi econòmic

Mentre que l'AMA diu:

While physicians should be conscious of costs and not provide or prescribe unnecessary medical services, concern for the quality of care the patient receives should be the physician’s first consideration. This does not preclude the physician, individually or through medical or other organizations, from participating in policy-making with respect to social and economic issues affecting health care

Heu caigut al parany. La qüestió és una altra, correspon a un sindicat fer codis d'ètica?

Experiments, comportament i MAOA

Si hi ha una branca de l'economia que creix notòriament és l'economia experimental i del comportament. I a partir d'avui és notícia a Barcelona perquè hi ha el congrés internacional sobre la qüestió, IMEBE.
Dels abstracts destaco aquest:

Genetic susceptibility for individual cooperation preferences: The role of monoamine oxidase a gene (MAOA) in the voluntary provision of public goods
Michele Griessmaier. University of Trier
Vanessa Mertins. University of Trier
Andrea Schote-Frese. University of Trier
Wolfgang Hoffeld. IAAEG. University of Trier
Jobst Meyer. University of Trier
Abstract
In the context of social dilemmas, previous research has shown that human cooperation is mainly based on the social norm of conditional cooperation. While in most cases individuals behave according to such a norm, deviant behavior is no exception. Recent research further suggests that heterogeneity in social behavior might be associated with varying genetic predispositions. In this study, we investigated the relationship between individuals' behavior in a public goods experiment and the promoter-region functional repeat polymorphism in the monoamine oxidase A gene (MAOA). In a dynamic setting of decreasing uncertainty, we were able to analyze differences in two main components of conditional cooperation, namely the players' own contribution and their beliefs regarding the contribution of other players. We showed that there are significant associations between individuals' behavior in a repeated public goods game and MAOA. Our results suggest that male carriers of the low activity alleles cooperate significantly less than those carrying the high activity alleles given a situation of high uncertainty. With decreasing uncertainty about the others' cooperativeness, the genetic effect diminishes. Furthermore, significant opposing effects for female subjects carrying two low activity alleles were observed.

Els aimants de la predicció del comportament social restaran satisfets, i d'altres com jo, ens mantindrem escèptics a l'espera de nous resultats. Cal dir que el tema del MAOA, el gen del guerrer, farà parlar.

The Good Doctor_ Why Medical Uncertainty Matters

 The Good Doctor_ Why Medical Uncertainty Matters

Controversies on QALYs

The Limitations of QALY: A Literature Review

After 50 years, valuing health using QALYs is still a daunting task. Basically the debate over ethical considerations, methodological issues and theoretical assumptions, and context or disease specific considerations is still alive. And I would add that it will remain as an open issue. Those that would like a simple metric for a complex issue will fail forever. And this pitfalls are translated to decision making when QALYs are the reference for resource allocation.
I'm unsure about what will be the next step. A recent article explains current limitations, but unfortunately I can't foresee alternative options for the future:

Debate continues to exist on whether QALYs should serve as the central means of health economics analysis. This review examines the potential shortfalls of QALYs, spanning current ethical, methodological, and contextual domains in addition to examining their suitability for regenerative medicine and future technologies. In the UK, NICE currently stipulates a threshold of £20 000 - £30 000 per QALY  when evaluating new therapeutics and/or technologies for NHS adoption, and has used this tool to apply a rational and transparent process to technological adoption for over ten years. Calculating QALY or cost effectiveness thresholds is particularly complex and debate has previously been publicized on whether the value of a QALY should be dictated by first proposing the worth of a QALY and setting the healthcare budget at or below that value, or alternatively, proposing a healthcare budget and then allowing the cost of a QALY to declare itself following purchasing decisions. With the advent of cellular based therapeutics and their comparably high upfront costs, the QALY calculation methodology may need refinement to realise the financial advantages and opportunity costs such interventions may convey – particularly considering the degree of uncertainty associated with them.

Meanwhile we should focus on improving comparative effectiveness of current and new technologies, specially those that are related to precision medicine.

 



 

Dr. Heisenberg's Magic Mirror of Uncertainty, 1998

Duan Michals exhibition in Barcelona

 

Health vs. wealth in a pandemic

HEALTH VS. WEALTH? PUBLIC HEALTH POLICIES AND THE ECONOMY DURING
COVID-19

A NBER paper says:

A pandemic can impact an economy in many ways: reductions in people’s willingness
to work, dislocations in consumption patterns and lower consumption, added stress on the financial system, and greater uncertainty leading to lower investment. These are
respectively referred to as (labor) supply shocks, demand shocks, financial shocks and
uncertainty shocks. Connected economies and epidemiological communities also move in synch. Even a healthy economy, or an economy that has not mandated a shutdown, may feel the impact of external events. With the exception of the 1918 influenza, recent
pandemics have neither had as large of a global impact, nor has there been as much real
time data available to empirically assess the economic and public health impact of NPIs.
We study outcomes during the Covid-19 pandemic.
We have three main results. First, our analysis shows NPIs may have been effective
in slowing the growth rate of confirmed cases of Covid-19 but not in decreasing the growth rate of cumulative mortality. Second, we find evidence of spillovers. NPIs may have impacts on other jurisdictions. Finally, there is little evidence that NPIs are associated with larger declines in local economic activity than in places without NPIs.

Trade-offs in algorithmic clinical decision making

On the ethics of algorithmic decision-making in healthcare

Great article.

Clinicians, or their respective healthcare institutions, are facing a dilemma: while there is plenty of evidence of machine learning algorithms outsmarting their human counterparts, their deployment comes at the costs of high degrees of uncertainty. On epistemic grounds, relevant uncertainty promotes risk-averse decision-making among clinicians, which then might lead to impoverished medical diagnosis. From an ethical perspective, deferring to machine learning algorithms blurs the attribution of accountability and imposes health risks to patients. Furthermore, the deployment of machine learning might also foster a shift of norms within healthcare. It needs to be pointed out, however, that none of the issues we discussed presents a knockout argument against deploying machine learning in medicine.

Option value of healthcare technologies

 Broadening the Concept of Value: A Scoping Review on the Option Value of Medical Technologies

Key messages, 

Traditionally, cost-effectiveness analyses have been conducted from the payer perspective, although the question of whether they should be expanded to take a broader perspective continues to animate a lively debate. Lately, the attention has focused on wider components of benefits, including the so-called  option value. Our scoping review provides a comprehensive synthesis of conceptual and empirical aspects related to this topic recently introduced in the value assessment framework debate.

From a conceptual standpoint, the coexistence of 3 distinct definitions of option value in the literature emerging from our scoping review urges us to advocate for greater clarity of language in future research. We recommend using “insurance value” when referring to the utility of knowing that one may have access to a healthcare service should one need it in the future, as in definition A. Definition B mainly relates to decision making under uncertainty and specifically to the value of deferring uncertain unrecoverable decisions to a later time. In the evaluation of healthcare technologies and programs, this dimension of value originates from the possibility of delaying a reimbursement/adoption decision, if there is an expectation that better information on a technology’s (cost-) effectiveness will become  available in the future—for example, because a new clinical trial reports its results. Because this definition is rooted in financial options theory and its application to capital investment decisions, we recommend using the term “real option value,” consistently with the terminology used outside the healthcare sector 

According to the third definition, the claimed value does not originate from the uncertainty around a decision and the flexibility of deferring it, as in definition B, but rather it stems from the consideration that the value of a life-extending technology should also include the benefits of future treatments that otherwise would be precluded to patients if they did not benefit from improved survival. This definition of value pertains to the broader discussion on whether future costs and benefits not directly linked to the intervention being assessed should be accounted for when evaluating a technology.Therefore, we recommend that research related to this definition adopt the term “option value of survival.”

To date, no consensus has been reached yet

Les escaliers de la rue Chappe  à Montmartre.

The threshold strategy for decision making

When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation

Physicians are often forced to act (e.g. order a diagnostic test or prescribe treatment) in face of  diagnostic uncertainty. Theories of decision-making indicate that physicians should act when the benefit of such an action outweighs its harms (for a given probability of disease). According to the threshold model when faced with uncertainty about whether to treat, order a test, or simply observe the patient, there may exist some probability of disease at which a physician is indifferent  between administering versus not administering treatment and ordering versus not ordering a diagnostic test . These are known as the treatment threshold, the test-treatment threshold and testing threshold, respectively.

 If physicians estimate treatment benefits, treatment harms, and test performance similarly, and integrate those into a threshold which they heed, this would result in more uniform medical practice. However, a vast body of empirical research has demonstrated significant variation in medical practice: seemingly similar patients are treated differently by diferent physicians.

Why is this so?. The authors explain in the article the differences between normative thresholds and descriptive ones and what to do about it: change the perspective - ‘target decision making, not geography"-. (?). A must read.

We demonstrate here that the threshold concept ultimately relates to the question of rational decision-making. Surprisingly, however, little empirical work has been published on the threshold models, or using the threshold concept as a theoretical platform to investigate clinical decision-making. This calls for the renewed interest in comparing ‘derived [or descriptive] thresholds with prescriptive thresholds obtained by decision analysis’, the call which was issued almost 30 years ago but left unheeded probably because of the lack of theoretical developments. However, the last 30–40 years have seen remarkable theoretical developments in the fields of cognitive sciences and decision-making such as dual-processing theories that have emerged as the important contenders for redefinition of rational choice. Understanding which theory underpins physicians’ and patients’ decision-making must be a key policy and research priority.

Uncertainty and regret in medicine

The Power of Regret

While reading NEJM I find an article on regret:

As physicians, we are acutely aware of the element of uncertainty in medicine, but we less often recognize its close companion, regret. Regret in all its forms can be a powerful undercurrent, moving patients to act in ways that may baffle us.

Kahneman and Tversky said  that bad outcomes from recent action are more regretted than similar outcomes from inertia. There two types of bias that affect regret. Omission bias is the tendency toward inaction or inertia — reflects anticipated regret. Commission bias is the tendency to believe that action is better than inaction, and can result in regret arriving later when a bad outcome occurs.

When we’re in pain or acutely anxious, we are “hot” and apt to make choices that we imagine will rapidly remedy our condition, which predisposes us to commission bias. In a hot state, patients may discount too deeply the risks posed by a treatment and overestimate its likelihood for success, paving the way for later regret if the outcome is poor. Patients who choose elective procedures while in a hot
state and end up with a bad outcome may be at particular risk for regret due to commission bias.

Georges Seurat. Two Sailboats at Grandcamp (Deux voiliers à Grandcamp), c. 1885.
Oil on panel, BF1153. Public Domain. Barnes Foundation

How epidemic-macroeconomic models of pandemic create uncertainty

Dealing with Covid-19: understanding the policy choices

A model is as good as its assumptions!. This is obvious and the application requires good data. Both issues, assumptions and data are the reasons why many models doesn't fit in this pandemic. Bad assumptions and bad data give bad conclusions. Have a look at this paper and in p.5 you'll find the different health and economic impact of models under different assumptions. So different that require a clever explanation if somebody wants to use them to take a decision.

VSL-based and SIR-macro models have helped to inform policy decisions in the early stages of the Covid-19 pandemic. However, the existing models are subject to a number of caveats, particularly relating to the uncertainty of their underlying epidemiological projections and stylised economic foundations.

 Juan Genovés

The uncertainty over genomics sequencing value in clinical decision making

Assessing Genomic Sequencing Information for Health Care Decision Making: Workshop Summary

"The value of genetic sequence information will depend on how it is used in the clinic", key statement that needs some elaboration. This is precisely what the IOM report does, you'll find in their pages the current situation about how genomics may impact in decision making. In chapter 5 you'll understand how an insurer decides about coverage of such tests according to 5 criteria:

1. The test or treatment must have final approval from appropriate governmental regulatory bodies, where required;
2. scientific evidence must permit conclusions about its effect on medical outcomes;
3. technology must improve net health outcomes;
4. the technology must provide as much health benefit as established alternatives; and
5. the improvement in health must be attainable outside investigational settings.

Unfortunately, if you start from the first one, you'll find a complete lack of references by governmental bodies on the approval of such tests. Therefore, I can't understand from the chapter how successful they are on such process.
While reading the book you'll increase your uncertainty about outcomes and value of genomic tests instead of reducing it. This was my impression. Let's wait for future good news, again.

PS. Summary of the report:
"Clinical use of DNA sequencing relies on identifying linkages between diseases and genetic variants or groups of variants. More than 140,000 germline mutations have been submitted to the Human Gene Mutation Database and almost 12,000 single nucleotide polymorphisms have currently been associated with various diseases, including Alzheimer’s and type 2 diabetes, but the majority of associations have not been rigorously confirmed and may play only a minor role in disease. Because of the lack of evidence available for assessing variants, evaluation bodies have made few recommendations for the use of genetic tests in health care."

El disseny de sistemes de pagament

 A Framework for the Design of Risk-Adjustment Models in Health Care Provider Payment Systems

A partir d'avui aquest blog es trasllada a Substack. Durant unes setmanes serà accessible simultàniament per blogger i per substack. Anoteu l'adreça: econsalut.substack.com

Article resumit amb IA.

Aquest article presenta un marc conceptual integral per al disseny de models d'ajust de risc (RA) en el context de models de pagament prospectiu a proveïdors d'assistència sanitària. L'objectiu és desenvolupar un marc que expliciti les opcions de disseny i les compensacions associades per tal de personalitzar el disseny de l'RA als sistemes de pagament a proveïdors, tenint en compte els objectius i les característiques del context d'interès.

Introducció (1-3): Durant les últimes dècades, els reguladors i els responsables polítics de la salut han fet esforços per millorar l'eficiència de la prestació d'assistència sanitària mitjançant la reforma dels sistemes de pagament a proveïdors. Específicament, l'eficiència s'ha perseguit mitjançant la introducció d'elements prospectius en els models de pagament, donant lloc a diversos Models de Pagament Alternatius (MPA) com els acords de qualitat alternatius i els pagaments agrupats. Aquests MPA tenen com a objectiu incentivar l'eficiència traslladant (part de) la responsabilitat financera dels pagadors als proveïdors. Una característica típica dels pagaments prospectius a proveïdors és que es basen en un "nivell de despesa normatiu" per a la prestació d'un conjunt predefinit de serveis a una determinada població de pacients. El nivell de despesa normatiu es refereix al nivell de despesa que "hauria de ser" depenent de la població de pacients d'un proveïdor, en lloc de la despesa observada. Un element clau en la determinació dels nivells de despesa normatius és la correcció de les diferències sistemàtiques en les necessitats d'assistència sanitària de les poblacions de pacients dels proveïdors, comunament coneguda com a ajust de risc (RA). L'RA és crucial per garantir un terreny de joc igualitari per als proveïdors i per evitar incentius per a comportaments no desitjats, com la selecció de riscos.

Nova Contribució (8-10): Tot i les contribucions conceptuals existents sobre el disseny de l'RA, actualment no hi ha un marc integral per adaptar el disseny de l'RA al pagament de proveïdors i a les característiques essencials del context. Aquest article desenvolupa aquest marc sintetitzant, ampliant i aplicant coneixements de la literatura existent. La metodologia va incloure una revisió de la literatura combinada amb consultes a experts en el camp de l'RA i els sistemes de pagament. La informació recopilada es va sintetitzar per desenvolupar el marc, del qual van sorgir tres criteris per al disseny de models d'RA i es van agrupar les opcions i les compensacions en dues dimensions principals: (a) la tria dels ajustadors de risc i (b) la tria de les ponderacions de pagament.

Definicions de Conceptes Clau (11-13): Els models de pagament prospectiu i els MPA traslladen la responsabilitat financera dels pagadors als proveïdors per tal d'incentivar el control de costos i l'eficiència. Qualsevol trasllat de responsabilitat financera requereix que el pagador determini el nivell de despesa normatiu, que reflecteix el nivell de despesa apropiat donades les necessitats d'assistència sanitària d'una població i els objectius dels MPA. El nivell de despesa normatiu no fa referència necessàriament al nivell de despesa absolut o òptim, sinó al nivell considerat apropiat donat el nivell/objectius d'eficiència perseguits pel MPA.

Fonts de Variació de la Despesa i el Paper de l'RA i la Mancomunació de Riscos (14-19): Quan s'estableixen nivells de despesa normatius, és important considerar tres fonts de variació de la despesa: (a) variació sistemàtica impulsada per factors fora del control dels proveïdors (variables C o "factors de compensació"), (b) variació sistemàtica impulsada per factors que els proveïdors poden influir (variables R o "factors de responsabilitat"), i (c) variació aleatòria. Per evitar que els proveïdors assumeixin riscos excessius que no poden influir, els MPA solen aplicar alguna forma de mancomunació de riscos. L'RA prospectiu s'utilitza per compensar la variació de la despesa deguda a les variables C. La naturalesa i el grau en què s'ha de compensar la variació de la despesa resultant de les variables C forma el punt de partida d'un model d'RA.

Tres Criteris per al Disseny de Models d'RA (19-26): L'objectiu general de l'RA en els MPA és compensar els proveïdors per la variació de la despesa deguda a les variables C, alhora que els manté responsables de la variació de la despesa deguda a les variables R. Això implica dos criteris clau: (a) compensació adequada per a les variables C i (b) cap compensació per a les variables R. Un tercer criteri important és la viabilitat.

• Criteri 1: Compensació Adequada per a les Variables C (20-26): Per evitar problemes de selecció, l'RA hauria de compensar adequadament les variables C que són rellevants a la llum de les possibles accions de selecció de riscos per part dels proveïdors (atraure/dissuadir pacients sans/no sans). També hauria de compensar les variables C que varien entre les poblacions de proveïdors per evitar la participació selectiva en el MPA.
• Criteri 2: Cap Compensació per a les Variables R (26-29): Per evitar ineficiències, l'RA no hauria de compensar les variables R. La compensació per la variació de la despesa de les variables R pot donar lloc a problemes d'eficiència, com la perpetuació de les ineficiències existents ("biaix d'status quo") i la creació d'incentius per a noves ineficiències (reducció dels incentius per al control de volum i preu, codificació ascendent).
• Criteri 3: Viabilitat (29-30): Un tercer criteri crucial és la viabilitat, que inclou la disponibilitat de dades i l'acceptació per part de totes les parts interessades (pacients, proveïdors, pagadors, reguladors).

Un Marc per al Disseny de Models d'RA (30-31): Aquest marc distingeix entre preguntes de disseny, opcions associades i consideracions i compensacions clau pel que fa a (a) la tria dels ajustadors de risc i (b) la tria de les ponderacions de pagament.

La Tria dels Ajustadors de Risc (31-47): Aquesta secció aborda tres preguntes principals de disseny:

• Quin tipus d'informació es basa els ajustadors de risc? (32-38): Les opcions inclouen informació demogràfica, socioeconòmica, subjectiva (de salut), diagnòstica, d'utilització, clínica, de despesa (retardada) i del costat de l'oferta. L'ús d'informació endògena (diagnòstics, utilització, despesa) és altament predictiu de la despesa de tipus C, però pot perpetuar ineficiències i introduir nous incentius perversos per al volum i el preu. L'ús d'informació exògena (demogràfica, socioeconòmica) no manté ni introdueix incentius perversos relacionats amb el volum o el preu, però el seu poder predictiu és generalment baix.
• A quin període de temps (període base) pertany la informació? (38-45): Es pot distingir entre ajustadors concurrrents i prospectius. Els efectes d'incentiu relatius d'aquestes opcions no estan clars a priori.
• Com dissenyar els ajustadors de risc? (46-47): Això inclou l'especificació de l'escala de mesura, l'operacionalització dels ajustadors (considerant condicions, jerarquies, restriccions) i les interaccions entre ajustadors.

La Tria de les Ponderacions de Pagament (48-60): Per trobar ponderacions de pagament apropiades, els responsables de la presa de decisions s'enfronten a tres decisions principals de disseny:

• Quina mostra d'estimació? (49-52): Es requereix una mostra d'estimació representativa de la població d'interès i dels nivells de despesa normatius. En la pràctica, sovint s'utilitzen dades històriques i poblacions de pacients similars.
• Quines intervencions de dades? (52-58): Quan la mostra d'estimació no és representativa, s'han de considerar intervencions de dades sobre la població de pacients i/o les dades de despesa per millorar la coincidència amb la població d'interès i el nivell de despesa normatiu. Això pot incloure correccions per biaixos i inequitats.
• Com derivar les ponderacions de pagament? (59-60): Això implica decidir quins ajustadors de risc incloure (considerant el biaix de la variable omesa) i quin criteri d'optimització utilitzar per estimar aquestes ponderacions. Les opcions van des de criteris d'optimització estàndard (OLS, GLM) fins a criteris personalitzats (regressió restringida, aprenentatge automàtic).

La Interconnexió Entre les Opcions de Disseny per als Ajustadors de Risc i les Ponderacions de Pagament (61-62): Les decisions de disseny dins i entre aquests dos temes estan altament interrelacionades. Per exemple, la tria de la informació en què es basen els ajustadors de risc afectarà la seva especificació i operacionalització. De la mateixa manera, les decisions sobre com es deriven les ponderacions de pagament depenen tant de la tria dels ajustadors de risc com de la tria de la mostra d'estimació (modificada).

Discussió (63-68): No hi ha un enfocament únic per al disseny de models d'RA, i el disseny adequat pot variar segons la configuració i les evolucions al llarg del temps. És crucial la decisió normativa sobre quines variables es consideren C i quines R. L'abast de la preocupació pels possibles incentius de selecció i control de costos pot variar segons el context. Les consideracions de viabilitat, com la disponibilitat de dades i l'acceptació de les parts interessades, també són importants.

Consideracions Més Amplies per al Disseny de l'RA en el Finançament de l'Assistència Sanitària (69-70): Tot i que aquest article se centra en el pagament a proveïdors, el marc proposat també podria beneficiar altres reformes de finançament, com les iniciatives de participació del consumidor, tot i que es necessita més recerca.

Conclusió (71): El disseny de models d'RA per a sistemes de pagament prospectiu a proveïdors és un exercici complex que requereix una consideració explícita de moltes preguntes, opcions i compensacions difícils. El procés de disseny ha de guiar-se per tres criteris clau: compensació adequada de les variables C, cap compensació de les variables R i viabilitat. Les diverses preguntes i opcions de disseny es poden classificar en la tria dels ajustadors de risc i la tria de les ponderacions de pagament. Es necessita més recerca per donar suport a les decisions normatives sobre les variables C i R, així com per desenvolupar mètriques d'avaluació integrals per a la valoració dels efectes dels incentius.

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The p53 nightmare

p53 and Me

This week you'll find a short piece in NEJM, a story written by a physician on how detecting a genetic p53 mutation changed her views. Key message:

Genetic knowledge is power only if both clinician and patient are equipped to move beyond a result and toward action, even if that merely means living well with what we know. I believe we need an expanded definition of genetic counseling; we require more data, yes, but also more sophisticated and sensitive ways of assimilating such data. And not just into databases we can mine to see what happens to people like me, but into programs for learning to live with uncertainty.

A must read

Predictive modeling in health care (2)

Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes

How do you want to manage, with a rearview mirror or just looking forward? Big data allows to look forward with better precision. The uncertainty about the disease and about the cost of care is large when you enter in hospital from an emergency department. But, after the diagnosis (morbidity), could we estimate how much could cost an episode?. If so, then we could compare the expected cost and the observed cost on a continous process.
Right now this is possible. Check this article that we have just published and you'll understand that costs of different services according to morbidity can be reckoned and introduced in health management. This analysis goes beyong our former article, much more general. So, what are we waiting for? Big data is knocking at the door of health care management, predictive modeling is the tool.

Amazing concert by Caravan Palace in Sant Feliu de Guixols three weeks ago.

The narrative of pandemics (2)

Información científica especializada, información pública y medios de comunicación durante la crisis del coronavirus

Today you'll find our article on communication in pandemic times in Blog Economía y Salud AES, how markets of attention and radical uncertainty drive current situation.

David Hockney

El valor d'un any de vida

 VALUING QALY GAINS BY APPLYING A SOCIETAL PERSPECTIVE

D'ençà que es varen formular els QALYs aprofitant la teoria de la decisió i la utilitat esperada, varen aixecar una gran expectativa. Vegeu-ne aquesta revisió a Value in Health. Però alhora la metodologia ha estat objecte de controvèrsia continuada. Llegeixo a Health Economics un article recent que aposta per la valoració social dels anys de vida ajustats per qualitat i ho fa amb una estimació empírica de la disponibilitat a pagar. Aquest és el resum:

Interpreting the outcomes of cost utility analyses requires an appropriately defined threshold for costs per quality-adjusted life year (QALY). A common view is that the threshold should represent the (consumption) value a society attaches to a QALY. So far, individual valuations of personal health gains have mainly been studied rather than potentially relevant social values. In this study, we present the first direct empirical estimates of the willingness to pay for a QALY from a societal perspective. We used the contingent valuation approach, valuing QALYs under uncertainty and correcting for probability weighting. The estimates obtained in a representative sample of the Dutch population (n = 1004) range from €52,000 to €83,000, depending on the specification of the societal perspective.

I tornem a ser on érem. Mitjançant l'estimació d'uns escenaris d'estat de salut (29) en el marc del controvertit qüestionari EQ-5D, s'arriba a unes disponibilitats a pagar que no podem saber-ne amb profunditat si es corresponen amb el valor social. Entre d'altres coses perquè la gent valora els escenaris en funció de si es troba en ells, si si ha trobat o si pot trobar-s'hi en el futur. I això és molt difícil d'ajustar. I sé que ho han fet el millor que han sabut i pogut, però no em convenç. Això vol dir que cal seguir cercant o deixar-ho empíricament al regulador enlloc de preguntar a la gent.

PS. Suggeriment. Feu un cop d'ull a l'article recent d'en Josep Maria Via.  La reflexió és oportuna, convé comprendre millor quina és l'eficiència abans de decidir si cal optar per formes organitzatives de control administratiu, o d'auditoria financera.
Tot i així hi ha una peça que falta. A més d'altres aspectes, l'error governamental inicial va ser no incloure la compensació acurada per amortització i noves inversions dins el sistema de pagament hospitalari. Al mantenir-ho fora del sistema, les subvencions a la inversió en els hospitals concertats van ser una eina clientelar per uns i altres que ha acabat en majoria pública del capital dels hospitals afectats. Convé revertir l'error inicial, situar les coses al seu lloc, i incentivar acuradament per assolir major valor.

Ho vaig dir fa dies. Ara en un pin.
En vull un!